Artificial intelligence always falls on fertile ground where there is data from which it can learn.
In short, e-commerce works in two steps: First, providers have to attract potential customers to their pages, i.e., generate traffic. Once the visitors have made it into the online shop, they have to be converted to customers. Artificial intelligence is already omnipresent in online marketing. Evermore intelligent algorithms attract the attention of online shop visitors and entice them to click on a special offer.
The second step – converting the visitor to the customer – is increasingly being permeated by AI. But how exactly can conversion rates be increased? And how can artificial intelligence influence the supposedly rational decision of online shop visitors to make a purchase?
Product Recommendations: The Right Offer For Every User
The algorithm behind the video suggestions on YouTube is now so precise that users no longer notice how the one video they wanted to watch quickly turns into five. It’s similar in e-commerce: those who suggest the right product to their customers at the right moment can massively enlarge their shopping carts. The best proof: Amazon consistently builds product suggestions into every step of its customer journey. Thanks to artificial intelligence, both the proposal’s quality and the submission time can be optimized. For example, it can make more sense to place hedonistically motivated suggestions at the beginning of the month since customers usually have more money available than at the end of the month.
Artificial Intelligence: Shopping Shouldn’t Be A Waste Of Time
For certain products such as groceries or everyday items, shopping is more of a routine than an experience, but you still have to do it. Previously, customers searched for each product individually in the online shop, selected it, and placed it in the shopping cart. Studies confirm that filling an online shopping cart often takes longer than shopping in the supermarket – even if you include the journey there.
In addition, offers that are too extensive are overwhelming for customers. The phenomenon of too extensive a choice is known as the “Paradox of Choice” and was researched by the American psychology professor Barry Schwartz. According to Schwartz, as many options as possible between different products by no means necessarily mean added value for customers. Somewhat, having too many options diminishes one’s ability to make choices because of the fear of making wrong choices. Schwartz found that the fear of making a wrong purchase decision can be significantly reduced if the options for customers are kept to a reasonable extent.
Predictive Baskets Accelerate The Shopping Process
AI-based predictive baskets provide a remedy here. You analyze individual shopping behavior and also automatically detect trends in the conduct of all customers. From this, predictions are made about what the respective customer wants to buy today. For example, if a customer buys charcoal every two weeks, this is suggested at a corresponding frequency. But when autumn begins and fewer and fewer customers buy charcoal, the AI no longer displays the product. The shopping time can thus be reduced to a third. A positive side effect: the shopping carts get bigger because no products are forgotten.
Artificial Intelligence Takes Customer-Centricity To A New Level
Because of its wealth of interaction data, e-commerce is the ideal field of application for AI. Some applications are already in practice, but many more are likely to follow in the future. They all help to improve the shopping experience for the customer further. Regardless of whether this improvement is perceived consciously or unconsciously: In the long term, this creates a bond with the shop that “understands” the customer best. Here lies the opportunity for online users to recognize AI as a growth lever, use it in a targeted manner, and thus leave the competition behind.
Also Read: The Future Of E-Commerce: What Challenges Retailers Expect
